def test_write_day_and_id(self):
result = self.writer.write(self.dest, self.trading_days, self.assets)
idx = 0
ids = result['id']
days = result['day']
for asset_id in self.assets:
for date in self.dates_for_asset(asset_id):
self.assertEqual(ids[idx], asset_id)
self.assertEqual(date, seconds_to_timestamp(days[idx]))
idx += 1
def apply_adjustments(self, dates, assets, baseline_values, adjustments):
min_date, max_date = dates[[0, -1]]
values = baseline_values.copy()
for eff_date_secs, ratio, sid in adjustments.itertuples(index=False):
eff_date = seconds_to_timestamp(eff_date_secs)
if eff_date < min_date or eff_date > max_date:
continue
eff_date_loc = dates.get_loc(eff_date)
asset_col = assets.get_loc(sid)
# Apply ratio multiplicatively to the asset column on all rows
# **strictly less** than the adjustment effective date. Note that
# this will be a no-op in the case that the effective date is the
# first entry in dates.
values[:eff_date_loc, asset_col] *= ratio
return values
def apply_adjustments(self, dates, assets, baseline_values, adjustments):
min_date, max_date = dates[[0, -1]]
values = baseline_values.copy()
for eff_date_secs, ratio, sid in adjustments.itertuples(index=False):
eff_date = seconds_to_timestamp(eff_date_secs)
if eff_date < min_date or eff_date > max_date:
continue
eff_date_loc = dates.get_loc(eff_date)
asset_col = assets.get_loc(sid)
# Apply ratio multiplicatively to the asset column on all rows
# **strictly less** than the adjustment effective date. Note that
# this will be a no-op in the case that the effective date is the
# first entry in dates.
values[:eff_date_loc, asset_col] *= ratio
return values
def apply_adjustments(self, dates, assets, baseline_values, adjustments):
min_date, max_date = dates[[0, -1]]
# HACK: Simulate the coercion to float64 we do in adjusted_array. This
# should be removed when AdjustedArray properly supports
# non-floating-point types.
orig_dtype = baseline_values.dtype
values = baseline_values.astype(float64).copy()
for eff_date_secs, ratio, sid in adjustments.itertuples(index=False):
eff_date = seconds_to_timestamp(eff_date_secs)
# Don't apply adjustments that aren't in the current date range.
if eff_date not in dates:
continue
eff_date_loc = dates.get_loc(eff_date)
asset_col = assets.get_loc(sid)
# Apply ratio multiplicatively to the asset column on all rows less
# than or equal adjustment effective date.
values[:eff_date_loc + 1, asset_col] *= ratio
return values.astype(orig_dtype)
